Feng Wu

Editor in Chief 
University of Science and Technology

Wenwu Zhu
Associate Editor-in-Chief
Tsinghua University Department of Computer Science

Zhu Li
Digital Communcations Associate Editor-in-Chief
Department of Computer Science and Electrical Engineering
University of Missouri

Volume 31 | Issue 4

IEEE Transactions on Circuits and Systems for Video Technology covers all aspects of visual information relating to video or that have the potential to impact future developments in the field of video technology and video systems, including but not limited to:

  1. (a) image/video processing: acquisition, representation, display, processing, transform, filtering, enhancement, restoration, watermarking;
  2. (b) image/video analysis and computer vision: characterization, classification, detection, tracking, assessment, segmentation, summarization, understanding, motion estimation, feature extraction, machine learning, machine intelligence, pattern analysis, pattern recognition, neural networks;
  3. (c) image/video compression: quantization, compression, quality assessment, rate control, error resilience, multiview, standards;
  4. (d) image/video communication: coding, streaming, distribution, interaction, networking, transport, wireless and mobile systems;
  5. (e) image/video storage: archives, networks, content management, databases, indexing, search, retrieval;
  6. (f) image/video hardware/software systems: architecture, hardware, software, multiprocessors, parallel processors, algorithms, VLSI, circuits, high-speed, real-time, low-power systems;
  7. (g) image/video applications: synthetic imaging, augmented imaging, video gaming, virtual reality, audio-visual systems, human-computer interaction, multimedia systems, multi-camera systems, surveillance, security, forensics, medical imaging, big data systems, cloud computing, and other video-related technologies.

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Presents the table of contents for this issue of the publication.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

Digital videos often contain visual distortions that are introduced by the camera's hardware or processing software during the capture process. These distortions often detract from a viewer's quality of experience. Understanding how human observers perceive the visual quality of digital videos is of great importance to camera designers. Thus, the development of automatic objective... Read more on IEEE Xplore

Blind image quality assessment (BIQA) aims to automatically predict the perceptual quality of a digital image without accessing its pristine reference. Previous studies mainly focus on extracting various quality-relevant image features. By contrast, the explorations on highly efficient learning model are still very limited. Motivated by the fact that it is difficult to approximate a complex and... Read more on IEEE Xplore

Detection of moving objects in videos is a crucial step toward successful surveillance and monitoring applications. A key component for such tasks is called background subtraction and tries to extract regions of interest from the image background for further processing or action. For this reason, its accuracy and real-time performance are of great significance. Although effective background... Read more on IEEE Xplore